V.K.Manupati, N.Arudhra, P.Vigneshwar, D.RajaShekar and M.Yaswanth

In this paper, a multi-objective based NSGA-II algorithm is proposed for dynamic job-shop scheduling problem (DJSP) with random job arrivals and machine breakdowns. In DJSP schedules are usually inevitable due to various unexpected disruptions. To handle this problem, it is necessary to select appropriate key machines at the beginning of the simulation instead of random selection. Thus, this paper seeks to address on approach called social network analysis method to identify the key machines of the addressed DJSP. With identified key machines, the effectiveness and stability of scheduling i.e., makespan and starting time deviations of the computational complex NP-hard problem has been solved with proposed multi-objective based hybrid NSGA-ll algorithm. Several experiments studies have been conducted and comparisons have been made to demonstrate the efficiency of the proposed approach with classical multiobjective based NSGA-II algorithm. The experimental results illustrate that the proposed method is very effective in various shop floor conditions

Social network analysis, NP hard, NSGA-II algorithm, Dynamic job-shop scheduling problem